Alexandre Termier

Shaping Up SHAP: Enhancing Stability through Layer-Wise Neighbor Selection

Machine learning techniques, such as deep learning and ensemble methods, are widely used in various domains due to their ability to handle complex real-world tasks. However, their black-box nature...

Generating robust counterfactual explanations

Counterfactual explanations have become a mainstay of the XAI field. This particularly intuitive statement allows the user to understand what small but necessary changes would have to be made to a...

XCM: An Explainable Convolutional Neural Network for Multivariate Time Series Classification

Multivariate Time Series (MTS) classification has gained importance over the past decade with the increase in the number of temporal datasets in multiple domains. The current state-of-the-art MTS...

XEM: An Explainable-by-Design Ensemble Method for Multivariate Time Series Classification

We present XEM, an eXplainable-by-design Ensemble method for Multivariate time series classification. XEM relies on a new hybrid ensemble method that combines an explicit boosting-bagging approach...

LCE: An Augmented Combination of Bagging and Boosting in Python

lcensemble is a high-performing, scalable and user-friendly Python package for the general tasks of classification and regression. The package implements Local Cascade Ensemble (LCE), a machine...

Discovering Useful Compact Sets of Sequential Rules in a Long Sequence

We are interested in understanding the underlying generation process for long sequences of symbolic events. To do so, we propose COSSU, an algorithm to mine small and meaningful sets of sequential...

Mining Periodic Patterns with a MDL Criterion

The quantity of event logs available is increasing rapidly, be they produced by industrial processes, computing systems, or life tracking, for instance. It is thus important to design effective...

HiPaR: Hierarchical Pattern-aided Regression

We introduce HiPaR, a novel pattern-aided regression method for tabular data containing both categorical and numerical attributes. HiPaR mines hybrid rules of the form $p \Rightarrow y = f(X)$...

Statistically Significant Discriminative Patterns Searching

Discriminative pattern mining is an essential task of data mining. This task aims to discover patterns which occur more frequently in a class than other classes in a class-labeled dataset. This...

Understanding Customer Attrition at an Individual Level: a New Model in Grocery Retail Context

Raising the Dead: Extending Evolutionary Algorithms with a Case-Based Memory

Toward a Framework for Seasonal Time Series Forecasting Using Clustering

Efficient Parallel Mining of Gradual Patterns on Multicore Processors

QuickFill : travailler plus pour générer moins en synthèse de programmes

Découverte d'itemsets fréquents fermés sur architecture multicoeurs

Visualiser des explications contrefactuelles pour des données tabulaires

PGP-mc : extraction parallèle efficace de motifs graduels

Compressing and Querying Skypattern Cubes